Call-Log App Aims to Reverse-Engineer NSA Surveillance

Why It Matters

Understanding what can be learned from call logs will inform discussions about NSA surveillance programs.

In an attempt to discover what the NSA can learn about people from the data it harvests from telecommunications companies, researchers at Stanford have set out to compile their own massive database of call and text logs—and they want you to help.

The MetaPhone project asks volunteers to install an Android app that sends the researchers copies of a device’s call logs and basic data from a person’s Facebook account. The researchers say that a large collection of such data will make it possible to use data-mining techniques to discover which aspects of people’s lives—as recorded in their Facebook data—can be revealed by examining just their calling and texting logs.

Those logs include what the NSA calls “metadata”—the time, duration, and source and origin numbers of every call. The agency says it searches its metadata collection only for specific phone numbers related to investigations, but opponents of the program claim that, with careful analysis, the database could be used to reveal personal details on a vast scale.

With details of the NSA’s data-analysis capabilities unknown, Jonathan Mayer, cofounder of the MetaPhone Project, says that a crowdsourced collection of metadata will add valuable hard evidence to the debate. “Some defenders of the NSA’s bulk collection programs have taken the position that metadata is not revealing,” he says. “We want to provide empirical evidence on the issue.”

The NSA metadata collection program excludes location information, but Mayer expects to find that many details from people’s lives can be deduced from their call and text patterns. “Our hypothesis is that phone metadata is packed with meaning.”

Preliminary results posted online this morning back up that claim. Using the small amount of data already collected by their app, Mayer and colleagues show that calling and texting patterns can reveal whether a person is in a relationship.

Doing that is harder than it might seem. Everyone has a number they call or text most often whether or not they are in a relationship. The researchers trained software to examine patterns in the frequency and duration of texts and calls for people whose Facebook status indicated that they were in a relationship. The software could then look at new call and text logs and correctly identify six out of 10 people in relationships.

Such findings may have influence beyond the realm of policy and legal debates about domestic surveillance. Telecommunications companies have begun analyzing metadata from their own customers for marketing purposes (see “How Wireless Carriers Are Monetizing Your Movements”). Some privacy campaigners say this practice should be examined by the U.S. Federal Trade Commission, which has begun to show a close interest in the use of data mining in recent years.